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The Impact of Hedge Fund Activism on the Target Firms
Existing Bondholders
April Klein* and Emanuel Zur**
This version: November 2009
*April KleinStern School of BusinessNew York University
(212) [email protected]
**Emanuel ZurZicklin School of Business
CUNY-Baruch College
(646) [email protected]
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The Impact of Hedge Fund Activism on the Target Firms Existing Bondholders
Abstract
In contrast to previous studies documenting positive abnormal returns to target shareholders, we
find that hedge fund activism significantly reduces existing bondholders wealth. Bondholders
earn an average excess bond return of -3.9% around the initial 13D filing date, and an additional
average excess bond return of -6.4% over the remaining year after the filing date. When
examining the reasons behind these results, we find that negative excess bond returns are related
to a subsequent decline in cash on hand (loss of collateral effects) and an increase in total debt as
a percentage of total assets. In addition, negative bond returns are more prominent when the
hedge fund activist conducts a confrontational campaign against the target firm or if the activist
gains at least one seat on the targets board within a year of the initial 13D filing. We also find
evidence of an expropriation of wealth from the bondholder to the shareholder. We conclude
that the intervention of the activist results in the firm taking actions that are deleterious to
bondholder wealth.
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I. Introduction
This paper examines the impact of hedge fund activism on existing bondholders by
examining a comprehensive sample of corporate bonds for U.S. firms that were targeted between
1994 and 2006. In contrast to Klein and Zur (2009) and Brav et al. (2008), who find that hedge
fund activism benefits target firm shareholders, we find that hedge fund activism significantly
reduces existing bondholders wealth. Bondholders earn a mean excess bond return of -3.9%
around the initial 13D filing date, and an additional average excess bond return of -6.4% over the
remaining year after the filing date.
We examine, in detail, the reasons behind these results. Consistent with prior studies on
determinants of credit risk, we find that the negative excess bond returns are related to a
subsequent decrease in cash on hand (loss of collateral effects) and an increase in total debt as a
percentage of total assets.1 In addition, bond returns are more negative when the hedge fund
activist conducts a confrontational campaign against the target firm, or if the activist gains at
least one seat on the targets board within a year of the initial 13D filing. We conclude that the
intervention of the activist results in the firm taking actions deleterious to bondholders.
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returns to shareholders to a reduction of free cash flow agency costs (Jensen, 1986).2
The positive returns to shareholders, coupled with the negative returns to bondholders,
suggest an expropriation of wealth from bondholders to shareholders. This is a valid depiction.
Specifically, they find that in the year subsequent to the initial 13D filing date, target firms, on
average, significantly decrease their cash on hand, double their dividends to common
shareholders and increase their debt-to-assets ratios. While these actions may be beneficial to
shareholders, they amount to a reduction in cash available for future interest and principal
payments to existing bondholders. This, along with the increase in leverage, suggests that more
creditors are competing for a smaller amount of cash on hand. Further, Klein and Zur (2009),
Brav et al. (2008), and Greenwood and Schor (2009) find that hedge fund activists elicit
substantial changes in the target firms following the initial 13D filing date. These changes
include an increased frequency of the company being merged or acquired, higher CEO turnover,
the activist obtaining seats on the targets boards of directors, and changes in the firms operating
strategies. While these actions may benefit shareholders, they also inject risk into the firm,
increasing the bondholders credit risk.
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bondholders. Previous papers have concentrated almost exclusively on the impact that hedge
fund activism has had on existing shareholders, reporting positive excess returns on the inception
and continuation of the activist campaign. This paper illustrates that what might be beneficial,
on average, for one set of stakeholders may not be beneficial for a different group. Specifically,
the better monitoring hypothesis of the firm put forth by these papers may not translate into
increased returns for the bondholder.
Second, our study sheds light on the previously reported positive abnormal shareholder
returns for the hedge fund target firm. Our finding of the negative association between excess
bond and excess stock returns presents a source of shareholder wealth from hedge fund activism
that has not been detected beforehand. We also present evidence that the unsystematic equity
risk increases as a result of the shareholder activism. Future work might want to consider how
this impacts shareholder value.
Our paper adds to the literature on credit ratings and overall bond risk. Hedge fund
activism results in a disproportionately high number of credit rating downgrades, a finding that
might be useful to policy makers and credit rating agencies in assessing the risks and perceived
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provides empirical evidence that hedge fund activism also results in a transfer of wealth from the
bondholder to the shareholder, both around and after the initial 13D filing.
The rest of the paper proceeds as follows. Section II describes our sample selection and
provides descriptive statistics for the hedge fund target and control samples. Section III contains
the excess bond returns around and subsequent to the initial 13D filing date. Section IV proposes
and tests for possible factors behind the negative bond returns. Section V presents the results on
possible expropriation effects from bondholder to shareholder. Section VI examines credit rating
changes. We conclude in Section VII.
II. Hedge Fund Activism: Sample Selection and Data Description
A. Sample
There is no legal definition of what a hedge fund is. In fact, many so-called hedge funds
do not engage in hedging activity to a great extent. Following previous papers, we define a
hedge fund as an investment vehicle that is relatively free from the regulatory controls of the
Securities Act of 1933, the Securities Exchange Act of 1934, and most notably the Investment
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from 17% (17/101) in 2006 to 100% (5/5) in 1994, with no discernable upward or downward
temporal pattern.
Panel B presents the most recent bond ratings prior to the filings of the initial 13Ds.
Bond ratings are taken from the WRDS Mergent Fixed Income Securities Database (Mergent
FISD). For the target firm sample, the ratings originate from three different bond rating agencies
Standard and Poors (S&P), Moodys, and Fitch. While most of the bonds in our sample are
rated by one agency only, there are a number of bonds that are rated by two or even three of the
bond rating agencies. When a firms bonds are rated by two or more agencies, we pick only one
rating our order of choosing is S&P followed by Moodys followed by Fitch.6
For the full sample, 190 of the 253 bonds (75%) are rated BB+/Ba1/BB+ or below (non-
investment grade), with only 63 bonds (25%) rated BBB-/Baa3/BBB- or above (investment
grade). Similarly, 152 bonds (79%) in the bond price sample are rated non-investment grade,
with the remaining 41 bonds (21%) rated investment grade. Therefore, most of the bonds in the
sample can be considered speculative prior to the 13D filing. No bond is rated A+/A1/A+ or
above; similarly, no bond is in default (D/Ca/D) at the time of the filing.
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significant at the 0.01 level, supporting the view that the hedge fund target firm sample hails
from a different distribution of bond ratings than all firms listed on the Mergent FISD. Our
results are also at odds with extant papers that examine large, random samples of bonds over the
same time period, for example, Blume, Lim and MacKinlay, 1998, Kliger and Sarig, 2000, Gan,
2004, and Easton, Monahan, and Vasvari, 2009.
B. Control Sample
We create a control sample of seasoned bonds by matching the hedge fund target firms
bond with another bond on the Mergent FISD on four sequential dimensions.7 First, for each
firm, we pull the sub-sample of all seasoned bonds that are in the same Fama-French 48 industry
classification as the target firm. Second, from that group, we choose those bonds that have the
same bond rating as the activist target bond on the initial 13D filing date. This ensures that the
overall risks of the target and control sample bonds are similar. Third, we pare down the
possible matches by keeping only those bonds with the same bond maturity, thereby controlling
for differences in bond returns attributable to the bond yield curve. Fourth, to control for
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as shown in Panels A and B of Table 1. We refer to this sample as the control sample throughout
the study.
Our matching technique is similar to, but more complex, than that used by Bessembinder
et al. (2009) in their study that evaluates the statistical properties of different measurements of
abnormal bond returns. Bessembinder et al. (2009) match by the credit bond rating only when
using daily bond returns (i.e., the TRACE dataset), but match by the credit bond rating and the
time-to-maturity when using monthly bond returns (i.e., the Lehman Brothers Bond Database).
They do not match by industry or by trading frequency.
C. Descriptive Statistics
Table 2, column 1 presents accounting-based data, market-based data, and various
dimensions of hedge fund activism for target firms with outstanding bonds. Variables that use
balance sheet or price data only are measured on the last day of the quarter ending prior to the
initial 13D filing date. Variables that combine income statement data with balance sheet data are
calculated over the one-year period ending on the quarter preceding the initial 13D filing date.
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We find, consistent with Klein and Zur (2009), that hedge fund targets have a positive
ROA (0.095) prior to the funds intervention and a healthy operating margin (0.195). Similar to
Klein and Zur (2009) and to Brav et al. (2008), we find that the sample firms have relatively low
market-to-book ratios; the mean [median] ratio is 1.607 [1.275]. The standard deviation of the
unlevered returns (asset risk) has a mean of 0.331, which is similar to the mean of 0.32 reported
by Billet, King and Mauer (2004), suggesting that the asset risk of our hedge fund target firms
are similar to the target acquisition firms used in their study. Finally, consistent with Klein and
Zur(2009) and with Brav et al. (2008), hedge fund targets have positive abnormal stock returns
prior to the initial 13D filing date, and more than one-half of the firms pay no common
dividends.
We also examine the activism style of the hedge fund; 81% of the hedge funds take a
confrontational position from the beginning of their activist campaigns 9 Consistent with Klein
and Zur (2009) and Brav et al. (2008), we find that the activists are successful in shaking up the
firm. Within the first twelve months of the initial 13D filing, 48% of the activists gain at least
one seat on the targets board, and 34% of the hedge funds initiate or threaten a proxy fight with
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We compare the hedge fund bond sample in column 1 to three groups: Hedge fund target
firms without outstanding bonds prior to the initial 13D filing date (Column 2; N=382; [635-
235]), control firms (Column 3; N=253), and all firms listed on the Compustat data at the time of
the 13D filing date (Column 4; N=64,223). Columns (2) through (4) show significance levels for
differences in means and medians between target firms with outstanding bonds (column 1) and
the sample for that column. For all tests, the t-statistics are for differences in means, assuming
unequal variances between samples. The Z-statistics are from a Wilcoxon signed rank test,
which does not require the assumption that the populations are normally distributed.
Somewhat surprisingly, there are few differences in firm characteristics or hedge fund
activism dimensions between target firms with (column 1) and without outstanding bonds
(column 2). Comparisons of the means and medians for total assets and the market-based
variables produce no statistically significant differences between groups. There are some
differences, however. As expected, hedge fund activist target firms with outstanding bonds have
a higher long-term-debt-to-assets ratio than targets without outstanding bonds. Targets with
outstanding bonds have less cash on hand, but are more profitable in terms of ROA and prior
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firms have more total assets, a higher ROA and pay more dividends on average. One interesting
finding is no discernible difference in the long-term debt-to-assets ratio between groups,
suggesting no need to further match by the companys leverage ratio.
Finally, to give the reader a flavor as to how our hedge fund targets compare to the
Compustat database, we present summary statistics for all firms covered by Compustat from
1994 through 2006. Not surprisingly, the average hedge funds target differs substantially from
the representative Compustat firm. Consistent with Klein and Zur (2009) and Brav et al. (2008),
hedge fund targets, on average, are smaller, have lower market-to-book ratios, and higher ROAs
than the representative Compustat firm. There are also differences in relative debt, cash on hand,
dividends paid, beta risk, and asset risk.
III. Bond Market Responses to Hedge Fund Activism
A. Computing Bond Returns: Data Used and Definitions
We compute short-run and long-run bond returns for each firm in the hedge fund activism
sample and for its control firm, respectively. The short-run bond return is the firms total bond
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many of our tests using the Trade Reporting and Compliance Engine (TRACE) database to
examine the robustness of our findings with respect to the database used. The primary advantage
of the Mergent FISD is that it has daily bond prices dating back to 1994, which spans our
sample. However, the database contains bond data on trades conducted by U.S. insurance
companies alone.10
There are several econometric issues involved in calculating bond returns. First, unlike
the equity markets, bond trading is relatively thin, with many bonds not trading for several days.
This sporadic trading will introduce noise into our bond return measures. To minimize the
staleness in the data due to non-trading, we eliminate the observation when calculating the short-
In contrast, the TRACE database covers a larger cross-section of daily bond
prices, but it contains data from July 1, 2002, thus limiting our study to a shorter time frame.
Easton, Monahan and Vasvari (2009) perform robustness checks on the two bond databases and
find that the pricing differences are minor, a finding consistent with institutional traders
dominating the bond trading market (Bessembinder et al., 2009). We note that several recent
published studies have used the Mergent FISD, for example, Campbell and Taksler (2003),
Davydenko and Strebulaev (2007) and Easton, Monahan and Vasvari (2009).
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Second, many firms have multiple bonds trading simultaneously. Two approaches in
calculating the sample and control samples bond return for a specific day are to use (1) the
weighted average of the firms multiple bond returns (e.g., Maxwell and Rao, 2003; Billet, King
and Mauer, 2004), or (2) to pick a random representative bond and use the return on that bond
only (e.g., Dhillon and Johnson, 1994).11
Third, Bessembinder et al. (2009) find that the statistical properties of bond returns are
better specified when using daily bond returns vis--vis monthly bond returns and for larger
sample sizes. They also report that non-parametric tests, for example the Wilcoxon signed rank
test, have more power than the parametric t-test; their study suggests that researchers include
both types of tests in their studies. In this study, we use daily bond returns, have a sample size
Given the complexity of our matching criteria for the
control sample, we present our findings by using a representative bond for both the sample and
target firms. To examine the sensitivity of our findings to this approach, we alternatively use
simpler matching criteria, i.e., industry and bond rating only, and calculate the daily bond returns
by using the weighted average multiple bond return approach. Results using the latter method
produce similar findings and, therefore, are not shown in the paper.
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testing for differences in the means and medians, respectively, between the target and control
firms. Panel A contains the results with the Mergent FISD and Panel B presents the returns
using TRACE data.
In Panel A, the target firms mean short-run raw bond return is -4.95%, significant at the
0.05 level, whereas the mean short-run bond raw return for the control firms is an insignificant -
1.03%. Testing for the difference in means produces a t-statistic of -3.27, significant at the 0.01
level. The median short-run raw bond return for the target firms is -2.13%, significant at the
0.10 level. This compares to an insignificant median raw bond return of -0.23% for the control
firms. Testing for difference in medians yields a Z-statistic of -2.43, significant at the 0.05 level.
We also calculate the abnormal bond return (untabulated), defined as the targets raw
return minus its control firms raw return. The mean short-run abnormal bond return is -3.91%;
its t-statistic is -2.68, significant at the 0.05 level. The median short-run abnormal bond return is
-1.86%, with a Z-statistic of -1.71, significant at the 0.10 level. In summary, we find evidence
that the advent of the hedge fund activist results in significantly negative returns to existing
bondholders.
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A comparison of the mean raw and abnormal bond returns to several prior bondholder
event studies reveals that the absolute value of the magnitude of the hedge fund target bond
returns is quite substantial. For example, Maxwell and Stephens (2003) report a mean raw bond
return of -0.11% (-11 basis points) around the announcement of a stock repurchase and Maxwell
and Rao (2003) find a mean excess monthly bond return of -0.878% (-88 basis points) around a
spin-off announcement. Billet, King, and Mauer (2004) report a mean excess bond return of
1.09% (109 basis points) for the target firm around a merger or acquisition announcement,
whereas Bessembinder et al. (2009) find a mean excess bond return of -0.20% (-20 basis points)
for the bidding firm. In fact, after examining over 20 prior abnormal bond return event studies,
Bessembinder et al. (2009) introduce shocks ranging from -/+ 2 basis points to no greater than -
/+ 50 basis points as being typical of an abnormal bond return.
In economic terms, bondholders lose, on average, $14.6 million (Mergent FISD) around
the Schedule 13D filing, which translates into an abnormal dollar return of $-11.2 million. Both
dollar returns are significant at the 0.01 level. Given that there are 189 firms in the sample, this
translates into a cumulative loss of $2.76 billion in raw bond returns and $2.12 billion in
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negative bond returns over the 13D filing period persist over the one-year period following the
13D filing date. Using the Mergent FISD, we find a mean [median] long-run bond return of -
6.42% [-5.84%] for the target firms; each significant at the 0.01 levels. In contrast, the control
sample has a mean [median] long-run bond return of -1.91% [-1.45%]; the former significant at
the 0.10 level. More importantly, testing for differences between the target and control groups
produce significant t- and Z-statistics (0.01 and 0.05 levels, respectively), supporting the
conclusion of a significantly negative excess long-run bond return for the target group.
The average long-run abnormal bond return (untabulated) is -4.48%, significant at the
0.01 level, and the median long-run abnormal bond return is -4.33%, significant at the 0.05 level.
Panel B produces similar results and conclusions with the TRACE data. 12
In dollar terms, using the Mergent FISD only, the average [median] long-run raw return
is -$18.9 million [-$16.13 million]; both are significant at the 0.01 level. The average abnormal
long-run bond return is -$14.8 million, and the median abnormal bond return is -$12.3 million;
both are significant at the 0.01 level. Thus, in dollar terms, the bondholder loses, on average,
Thus, we conclude
that the negative bond returns around the 13D filing date persist for at least one year.
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Figure 1 presents short-run (top line) and long-run (bottom line) raw bond returns by year
for the Mergent FISD sample only. There is a slight upward temporal pattern in the short-term
bond returns, with the average bond return moving from -5.31% in 1994 to -4.75% in 2006. To
see if this rise is statistically significant, we estimate a regression of annual short-run bond
returns on time.13
For the long-term raw bond returns, we notice an upward pattern from 1994 through
2001, and then a flat bond return of about -6% from 2002 through 2006. To examine the
significance of this trend, we estimate the same regression as shown in footnote 13, but with the
annual long-run bond return as the dependent variable. The coefficient, 1, for this regression is
0.093, with an insignificant t-statistic of 0.27. We conclude that no significant temporal pattern
exists for the long-run bond returns.
The coefficient, 1, is -0.017, with an insignificant t-statistic of -1.36; we
conclude that no significant temporal trend exists.
D2. Bond Returns by Initial Bond Rating
Figure 2 presents short-run (top line) and long-run (bottom line) raw bond returns by the
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Although there is no monotonic decline in bond returns and initial bond ratings, the
pattern in Figure 2 clearly demonstrates that non-investment grade bonds experience larger bond
price drops in the short- and long-run than investment grade bonds. The average short-run bond
return is -3.92% for investment grade bonds and -4.98% for non-investment grade bonds. A t-
test for the difference in means produces a t-statistic of 2.17, significant at the 0.05 level.
Similarly, the average long-run bond return for the investment grade bonds is -5.88%, but -
6.67% for the non-investment grade bonds. The t-statistic for difference in means by
investment/non-investment grade is -1.89, significant at the 0.10 level. Thus, there is initial
evidence that hedge fund activism affects non-investment bonds in a more adverse way.
D3. Abnormal Stock Returns
In Table 3, we present abnormal stock returns over the short-run and long-run periods.
Our motivation for tabulating abnormal stock returns is twofold. First, Klein and Zur (2009) and
Brav et al. (2008) report significantly positive abnormal stock returns around the initial 13D
filing date and over the following year.15 By calculating the abnormal stock returns for our
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and-hold value-weighted NYSE/AMEX/NASDAQ index from CRSP over the short or long-run
period (see Klein and Zur, 2009; and Brav et al., 2008). We test for statistical significance in two
ways. First, we calculate the t- or Z-statistic of the abnormal return itself. Second, we compare
the target firms abnormal return to the control samples abnormal return to see if they are
different from each other.
For both samples, shareholders earn positive mean [median] abnormal returns for the
period surrounding the initial 13D filing. In Panel A, the mean [median] short-run abnormal
stock return is 4.72% [3.67%], significant at the 0.01 [0.05] levels. In comparison, the control
samples abnormal stock returns are insignificantly different than zero. Testing for the
difference between target and sample mean or median yields a t-statistic of 4.40 and a Z-statistic
of 3.82; both are significant at the 0.01 levels. Panel B finds similar results using the TRACE
sample. Thus, unlike bondholders who, on average, earn abnormally negative short-run returns,
shareholders, on average, reap a positive benefit around the 13D filing. We also note that the
short-run stock returns are similar to those reported by Klein and Zur (2009) and Brav et al.
(2008) see footnote 15.
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We define the quarter in which the initial 13D filing is filed as quarter zero. We then
calculate the one-year change in the firms characteristic as the difference between the
aggregated four quarters afterthe initial Schedule 13D (quarters 1 through 4) and the aggregated
four quarters immediately prior to the filing (quarters -4 through -1). All accounting data are
from Compustat; market return data are from CRSP. All definitions of the variables are in the
Appendix.
Table 4 presents the results for both hedge fund target and control samples. Column (1)
contains the mean [median] ratios for the sample firms; column (2) presents the mean [median]
ratios for the control firms. We test for differences between columns (1) and (2) and indicate
through asterisks in column (1) whether the mean or medians are different between samples.
The findings in Table 4 are consistent with the proposition that hedge fund activists
change the structure of the target firm in many ways that are harmful to existing bondholders. In
terms of future earnings, there are statistically significant differences inEPS and EBITDA
between the target and control sample firms. Further, EPS and EBITDA drop for the target firms
whereas they increase for the control firms. The inferences surrounding changes in the
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with Kaplan and Urwitz (1979) and Blume, Lim, and MacKinlay (1998), who find an inverse
association with bond credit ratings and the long-term debt-to-assets and the total debt-to-assets
ratios.
When examining cash on hand, the mean [median]cash -to-assets ratio for the hedge
fund activism is -0.024 [-0.005]; this compares to 0.004 [0.000] for the control sample.
Including short-term investments to the cash balances results in a decrease in cash (more broadly
defined) for the target sample, but an increase for the control sample. The t- and Z-statistics for
differences between samples are significant at the 0.01 and 0.05 levels, respectively. Given that
cash and cash equivalents balances are the second most commonly cited factor by S&P in their
RatingsDirect Reports, these findings are consistent with the negative short-run and long-run
bond returns.16
We examine three ratios that help gauge the firms ability to pay off its debt and interest.
One explanation for the drop in cash can be gleaned by examining the one-year
change in dividends per share. Consistent with Klein and Zur (2009), we find that dividends per
share for hedge fund targets rise, on average, by 10.8 cents. This change in dividends is
significantly greater than the control firms dividend increase of 3.2 cents.
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comparison the control samples mean [median] change in 0.847 [0.029]. Testing for differences
between groups yields statistically significant test statistics, respectively, for both variables. In
contrast, we find no difference in FFO-to-debt between samples.
The last section of Table 4 contains other variables. Total assets for the target firms fall
by a mean [median] value of $104.157 [63.381] million, which is significantly different than the
increase of $461.186 [$132.910] million for the control firms. Thus, the overall collateral of the
target firms falls (see Kaplan and Urwitz, 1979 and Maxwell and Rao, 2003). In terms of market
risk, the unsystematic equity risk (()) rises significantly when compared with the control
sample. This finding is consistent with Kaplan and Urwitz (1979), who find an inverse
association between credit ratings and the firms equity risk. The asset risk of the firm
((Unlevered Returns)) increases significantly when compared to the control sample. In a
similar vein, Billet, King and Mauer (2004) report an inverse relation between the subsequent
change in the asset risk of the target or acquiring firm and excess bondholder returns.
In summary, hedge fund targets experience decreases in earnings, profitability, cash on
hand, and total assets within one year of the hedge fund intervention. Hedge fund targets also
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We regress short-run and long-run abnormal bond returns (Mergent FISD) on three types
of explanatory variables. First, we include changes in the target firms accounting and market
risk characteristics, similar to those described in Table 4. Second, we include two indicator
variables that relate to the bond itself. Kaplan and Urwitz (1979) find that subordinated debt,
ceteris paribus, have lower credit ratings. We therefore create an indicator variable based on
whether the representative bond is subordinated or not. For the sample of target firms, 17% of
the bonds are subordinated, compared to 7% of the control firms a difference in percentages
that is significant at the 0.01 level. We also create an indicator for whether the bond is rated
non-investment grade prior to the 13D filing. As we previously show, the majority of target firm
bonds are non-investment grade, and these bonds have more negative short- and long-run raw
returns.
Third, we include some explanatory variables that are specific to hedge fund activism
itself. We include indicators measuring whether the initial hedge fund activism is
confrontational, whether the hedge fund receives at least one seat on the targets board of
directors within a year of the original 13D filing, whether the hedge fund conducts or threatens a
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sample of activist targets, 31 (12%) have earnings announcements within the [-10, +1] window.
Thus, to eliminate a confounding event, we control for this type of event. Finally, to control for
possible temporal effects, we include time-dummy variables.
B2. Empirical Results
Table 5 presents results for the regressions on short-run abnormal bond returns (column
1) and long-run abnormal bond returns (column 2). As column 1 shows, short-run abnormal
bond returns are negatively and significantly related to (1) a confrontational hedge fund activism
style (Confrontational), (2) if the bond is non-investment grade, (3) the firms one-year change in
its total debt-to-assets ratio, and (4) whether there is a earnings announcement during the [-10,
+1] time period. Short-run abnormal bond returns are positively and significantly related to the
one-year change in the firms cash-and-investments-to-assets ratio.
The significantly negative coefficient on Confrontational is symmetrical with Brav et al.
(2008), Clifford (2008), Klein and Zur (2009), and Zur (2009), who report highershareholder
returns for confrontational activist campaigns vis--vis non-confrontational campaigns. The
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In contrast, we find no significant coefficients for changes in the market-to-book ratio,
ROA, dividends/share, the operating margin, Z-score, total assets, unsystematic equity risk, asset
risk, or whether the bond in subordinated. Nor do we find a significant coefficient on whether
the hedge fund gains a seat on the targets board, whether the hedge fund engages in a proxy
fight, or whether the target is merged or acquired with the next two years.
Column 2 presents the regression results for the long-run abnormal bond returns. Similar
to the regression on short-run abnormal bond returns, there are significantly negative coefficients
on Confrontational, Non-Investment Grade, andTotal Debt -to-Assets, and a significantly
positive coefficient onCash -plus-Investments-to-Assets. We also report a significantly
negative coefficient on Board, an indicator representing whether the activist gains at least one
seat on the targets board within a year.
In summary, hedge fund activism, on average, decreases bondholder wealth for a variety
of reasons. First, the subsequent reduction in cash on hand and the increase in the debt to assets
ratio increases the existing bondholders risk by reducing the firms collateral and placing more
debt on the firms balance sheet. Second, the type of hedge fund activism matters, with
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We examine the possibility that hedge fund activists expropriate wealth from
bondholders to shareholders during the course of the activism campaign. We articulate two
reasons for why this might occur. First, the hedge funds that we examine invest in the shares of
the target company; in fact, to be included in our sample, the hedge fund must have a beneficial
ownership at least 5% of the target firms shares. Thus, it is in the interest of the hedge fund to
pursue activities that benefit shareholders, even at the expense of the other stakeholders. Second,
we find significantly positive abnormal returns to shareholders around the initial 13D filing, but
significantly negative abnormal returns to bondholders, a finding consistent with an
expropriation effect.
Brav et al. (2008) briefly examine and rule out the alternative hypothesis that the
significantly positive shareholder returns they observe around the initial 13D filing date are due
to an expropriation of wealth from the bondholder to the shareholder. However, their conclusion
is based solely on comparing shareholder returns between targets that have no long-term debt to
those with some long-term debt. They report mean abnormal shareholder returns of 9.46% for
those firms with no long-term debt vs. 7.21% with those firms with some long-term debt, and
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regressions, a significantly negative coefficient on the abnormal stock return variable would be
consistent with the alternative hypothesis that an expropriation exists.
Table 6 presents the regression results. Columns (1) and (2) present the results with the
short-run abnormal returns. Columns (3) and (4) contain the results with the long-run abnormal
returns. Column (1) shows a significantly negative association between the short-run abnormal
bond return and the short-run abnormal stock return. The coefficient on short-run abnormal
stock return is -0.037, significant at the 0.01 level (t-statistic = -3.81). Thus, there is evidence
that shareholders expropriate wealth from the bondholder around the initial 13D filing date.
When we add the explanatory variables from Table 5, we find that (1) the coefficient on short-
run abnormal stock returns remains significantly negative, (2) the coefficients and significance
levels on the additional variables are similar to those reported in Table 5, and (3) the coefficient
and t-statistic for the abnormal stock return is similar to that reported in column (1). Thus, we
conclude that expropriation effect shown in column (1) is robust to the addition of the other
explanatory variables.
We also find a longer-run expropriation effect. In column (3), the coefficient on the
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abnormal bond return of -$14.84 [-$12.29] million. Thus, even over this longer time period, the
expropriation effects accounts for about one-quarter to one-third of the shareholders abnormal
return.
In summary, Table 6, in tandem with Table 3, provides evidence that the advent of the
hedge fund activist results in an expropriation of wealth from the existing bondholders to the
existing shareholders. This finding is new to the hedge fund activism literature in that it
examines both bondholder and shareholder returns. From the bondholders point of view, it
suggests that part of the loss in wealth is due to a transfer of wealth to the shareholder. In
particular, our findings illustrate that what may benefit one set of the firms claimants may be
detrimental to a second set of claimants.
VI. Additional Analyses: Changes in Bond Credit Ratings
We next examine whether the credit agencies modify their credit ratings for the bonds in
the year following the initial 13D filing. We have several reasons to expect a disproportionately
large number of credit downgrades for the hedge fund targets. First, the negative short-run and
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Panel A of Table 7 presents changes in credit ratings within one year of the initial 13D
filing for a both the hedge fund target and control firms. We present four events: a decrease
(Downgrade) in the bond rating, for example, from a B rating to a B- rating; an increase
(Upgrade) in the bond rating, for example, from a B rating to a B+ rating; a constant rating (No
Change); and a discontinued rating (Stop Rating).18
In contrast, 34 firms (13.4%) of the control sample have their bonds downgraded within
the same time frame, whereas 59 companies (23.3%) experience a bond upgrade. Eighty-nine
firms (35.2%) have no bond rating changes and 71 companies (28.1%) have their ratings
discontinued. To determine if the percentages of subsequent changes in bond ratings are similar
between sample and control firms, we conduct a Chi-square test on the percentage breakdowns
between the target and control firms. This test yields a 2 value of 76.80, significant at the 0.01
level, indicating that subsequent changes in bond ratings differ between hedge fund targets and
Seventy-four target firm bonds (29.3%) are
downgraded within a year of the initial 13D filing, whereas only 13 companies have their credit
ratings increased within a year (5.1%). Forty-one companies (16.2%) experience no change in
their bond ratings, and 125 firms (49.4%) have their ratings discontinued.
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Panel B presents the short-run and long-run abnormal bond returns by the subsequent
one-year rating change. As this panel illustrates, the short-run and long-run negative abnormal
bond returns are dominated by the group of firms that are downgraded within the year. The
average short-run abnormal bond return is -11.65% for the group of downgrades, compared to a
range of -0.31% to 4.92% for the other three groups. Similarly, the mean long-run abnormal
bond return for the downgraded bonds is -11.33%, compared to a range of -0.74% to 3.29% for
the other sub-samples. These findings are consistent with the bond market being efficient in that
the bond market anticipates and reacts to the eventual credit market downgrades. The efficiency
of the bond market is consistent with Hotchkiss and Ronen (2002), who examine the
informational efficiency of corporate bonds. The observed lead/lag relation between changes in
bond ratings and bond returns confirms those found by Katz (1974), Hettenhouse and Satoris
(1976) and Weinstein (1977), who look at this association over earlier time periods.
These findings suggest that the subsequent change in credit rating may be an additional
explanatory variable in the regressions on short-run and long-run abnormal bond returns that we
presented in Section IV (Table 5). Alternatively, the results are consistent with the proposition
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negatively related to a decrease in the firms cash and to an increase in total debt. Further, we
present evidence that some of these excess bond returns are the result of an expropriation of
wealth from the bondholder to the shareholder. Specifically, we document positive short-run and
long-run shareholder abnormal returns, and find a significantly negative association between
these shareholder returns and excess bondholder returns. We therefore conclude that although
the activism may be beneficial to shareholders, some of this benefit comes at the expense of the
existing bondholders.
We also find that the majority of the target firm bonds are rated non-investment grade
prior to the initial Schedule 13D filing. These bonds may be more vulnerable to the activists
actions as they are more likely to default than investment grade bonds. In support of this
contention, we document that short-run and long-run bond returns are more negative for non-
investment grade bonds, in both univariate and multivariate analyses.
Our study provides new insights into the hedge fund activism process. It is the first study
to examine the impact that hedge fund activism has on existing bondholder wealth. Our paper
also has implications for policy makers and for credit risk agencies by revealing a new factor,
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37
Appendix
Variable Definitions and Data Sources
Variable Definitions Data Sources
I. Bond DataShort-Run Bond Return is the short-run raw bond return around the initial Schedule 13D filing date
(t=0), calculated as:
10
101
0
+
=
+=
t
tct
t
BP
BPCBPBR
where, BPt+1 is the bond price on the first trading day after day zero. BPt-10 isthe price for the same bond for the earliest transaction that took place within10 calendar days prior to day zero. Ct is the sum of all coupon paymentsbetween day t-10 and day t+1. We eliminate the observation if the bond did
not trade during the [-30, +10] trading window. Mergent Fixed Income
Securities Database (FISD)
and
Trade Reporting andCompliance Engine Database(TRACE).
Long-Run Bond Return is the long-run raw bond return following the initial Schedule 13D filing date(t=0), calculated as:
1
1365
0
+
++
=
+=
t
tct
t
BP
BPCBPBR
where, BPt+365 is the bond price for the latest transaction that took placewithin 365 calendar days following day zero. BP t+1 is the bond price for thesame bond on the first trading day after day zero. C t is the sum of all couponpayments between days [+2, +365]. We eliminate the observation if the
bond did not trade during [+2, +10] and [+335, +395] trading windows.Short (Long)-Run AbnormalBond Return
is the difference between the sample firms and its control firms short(long)-run raw bond returns.
Subordinated Debt is an indicator = 1 when the target firm has subordinated debt in its capitalstructure, and = 0 otherwise.
Downgrade is an indicator = 1 when the bond rating decreased over the year followingthe initial Schedule 13D filing date, and = 0 otherwise.
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38
Upgrade is an indicator = 1 when the bond rating increased over the year followingthe initial Schedule 13D filing date, and = 0 otherwise.
No Change is an indicator = 1 when the bond rating did not change over the yearfollowing the initial Schedule 13D filing date, and = 0 otherwise.
Stop Rated is an indicator = 1 when the rating agencies stop rated the bond following theinitial Schedule 13D filing date, and = 0 otherwise.
Non-Investment GradeBond
is an indicator =1 if the bonds rating prior to the initial Schedule 13D filingdate is BB+ or lower, and = 0 otherwise.
II. Hedge Fund Data
Confrontational is an indicator = 1 when the hedge fund uses a confrontational activism style,and = 0 otherwise. Based on Klein and Zur (2009), we define the beginningof a confrontational activist campaign as the filing of an initial SECSchedule 13D, in which the activist clearly professes in the purpose
statement of the filing its goal to redirect managements efforts.
The investment activismstyle is from the Schedule13D filings.
Board representation and thethreat to start a proxy fightare from the popular press,using the Factiva database(formerly Dow JonesInteractive).
Board is an indicator = 1 when the hedge fund successfully appoints at least onemember to the board of its current investment within the year following theinitial Schedule 13D filing, and = 0 otherwise.
Proxy is an indicator variable = 1 when the hedge fund publicly threatens a proxyfight against its current investment within the year following the initialSchedule 13D filing, and = 0 otherwise.
M&A is an indicator variable = 1 if the target firm is merged or acquired withintwo years of the initial 13D filing, and = 0 otherwise.
CompustatIII.Target Firm characteristics and others
Short-Run Abnormal StockReturn
is the geometric raw return minus the value-weightedNYSE/AMEX/NASDAQ index over a window of [-10, +1] days, where day0 is the initial Schedule 13D filing date. Stock returns and the value-
weighted market index arefrom CRSPLong-Run Abnormal Stock
Returnis the geometric raw return minus the value-weightedNYSE/AMEX/NASDAQ index over a window of [+2, +365] days, whereday 0 is the initial Schedule 13D filing date.
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39
ROA is EBITDA (earnings before interest, taxes, depreciation and amortization)divided by total assets.
Accounting data are fromCOMPUSTATFundamentals Quarterly.
The balance sheet items arecalculated at the end of thequarter prior to the initialSchedule 13D filing. The incomestatement items are calculatedover the 4 quarters preceding theSchedule 13D filing date.
Operating Margin is EBITDA divided by sales.
Short-term Debt-to-Assets is the ratio of debt in current liabilities to total assets.
Long-term Debt-to-Assets is the ratio of total long-term debt to total assets.
Total Debt-to-Assets is the ratio of sum of the long and short-term debt to total assets.
Cash-to-Assets is total cash divided by total assets.
(Cash plus Investments)-to-Assets
is cash and short term investments divided by total assets.
Dividends per Share is the dividend per share-ex date.
Z-Score is the Altman (1968) model to determine the likelihood of bankruptcyamongst companies.
Total Assets are the total assets of the firm ($ Millions).
Market-to-Book is stock's market value of equity divided by the book value of total assetsminus total liabilities.
Beta is the coefficient of the error term from the market model estimation.
() is the standard deviation of the error term from the market model estimation.
(Unlevered Returns) is the standard deviation of unlevered monthly stock returns.
FFO is funds from operations.
EPS is the primary earnings per share excluding extraordinary items and
discontinued operations.
EBITDA is the earnings before interest, taxes, depreciation and amortization.
CFO is cash from operating activities.
Earnings Announcement is an indicator = 1 when the target firm announced earning during the eventstudy window, and = 0 otherwise.
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Panel B: Initial Bond Ratings by S&P/Moodys/Fitch
Rating (S&P/Moodys/Fitch)
Full Target
Bond Sample
Target Bond
Sample withBond Prices
Mergent
FISD
Investment GradeAAA/Aaa/AAA 0 0 1,537
AA+/Aa1/AA+ 0 0 364
AA/Aa2/AA 0 0 828
AA-/Aa3/AA- 0 0 1,373
A+/A1/A+ 0 0 1,669
A/A2/A 3 2 1,670
A-/A3/A- 16 9 1,405
BBB+/Baa1/BBB+ 12 8 1,424
BBB/Baa2/BBB2 14 10 1,374
BBB-/Baa3/BBB- 18 12 1,162
Total Number of Firms withInvestment Grade Bonds
63 41 12,806
Non-Investment GradeBB+/Ba1/BB+ 14 11 533
BB/Ba2/BB 18 14 551
BB-/Ba3/BB- 12 10 752
B+/B1/B+ 24 17 873
B/B2/B 30 24 1,359
B /B3/B 34 27 1 711
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Table 2
Characteristics of Target Firms Prior to the Initial 13D Filing Date
This table summarizes the characteristics of hedge fund target firms with outstanding bonds, hedge fund target firmswithout outstanding bonds, the control sample, and the entire COMPUSTAT population in the quarter prior to theinitial Schedule 13D filing date. For each variable the mean [median] is reported. All data are winsorized at the 1%and 99% levels. Columns (2)-(4) contain significance levels for differences between the means [medians] withcolumn (1). See Appendix for variable definitions. ***significant at the 0.01 level; **significant at the 0.05 level;*significant at the 0.10 level.
Hedge Fund TargetFirms with
Outstanding Bonds(1)
Hedge Fund TargetFirms without
Outstanding Bonds(2)
ControlFirms
(3)
COMPUSTATDatabase
(4)
Total Assets ($ Millions) 852.81[189.42]
947.29[210.16]
997.21*
[242.09]
2,354.636***
[230.821]**
Long-term Debt-to Assets 0.328[0.269]
0.265**
[0.247]*
0.339[0.305]
0.190***
[0.104]***
(Cash plus Investments)-to-Assets
0.108[0.086]
0.192***
[0.119]**
0.106[0.085]
0.171**[0.070]
ROA 0.095[0.105]
0.042**
[0.076]*
0.124*
[0.126]*
0.064*
[0.078]*
Operating Margin 0.195[0.146]
0.192[0.141]
0.179[0.134]
0.114**
[0.105]**
Market-to-Book 1.607
[1.275]
1.162
[1.074]
1.596
[1.173]
2.688***
[1.718]**Beta 0.814
[0.752]0.785
[0.736]0.789
[0.728]1.0335
**
[0.955]*
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Table 3
Short-Run and Long-Run Bond and Stock Returns
This table shows short- and long-run bond returns and the short- and long-run abnormal stock returns in theperiods surrounding and after the initial Schedule 13D filing date. Control firms are matched by industry,credit rating prior to the 13D filing, bond maturity, and trading frequency . Panel A presents the resultsbased on the Mergent FISD, while Panel B present the results based on the TRACE database. For eachvariable, the mean [median] is reported. The number of observations (N) reported is for the short/long-runrespectively. See Appendix for variable definitions. All data are winsorized at the 1% and 99% levels.***significant at the 0.01 level; **significant at the 0.05 level; *significant at the 0.10 level.
Panel A: Mergent Fixed Income Securities Database (Mergent FISD)
Hedge FundTarget Firms
Mean[Median]
Control FirmsMean
[Median]
t-statistic [Z-statistic] fordifference
between Columns(1) and (2)
(1) (2) (3)
Short-Run Bond Returns -4.95**[-2.13%]*
-1.03%[-0.23%]
-3.27***[-2.43]**
Long-Run Bond Returns -6.42%***[-5.84%]***
-1.91%*[-1.45%]
-3.39***[-2.52]**
Short-Run Abnormal Stock Returns 4.72%***[3.67%]**
1.11%[0.84%]
4.40***[3.82]***
Long -Run Abnormal Stock Returns 5.79%***
[4.62%]***
2.11%*
[2.01%]*
2.17**
[2.03]**
N(short-run/long-run) 189/193 189/193
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Table 4
One-Year Changes in Firm Characteristics for Hedge Fund Target
and Control Firm Samples
This table presents mean [median] one-year changes () in accounting and financial ratios for the sample of253 firms (column 1) targeted by hedge funds and their matching control firms (column 2). Change ismeasured over 4 quarters following the quarter of the initial 13D filing minus the 4 quarters preceding the13D filing. Control firms are matched by industry, credit rating prior to the 13D filing, bond maturity, and
trading frequency. For each variable, the mean [median] is reported. See the Appendix for variabledefinitions. All data are winsorized at the 1% and 99% levels. Column (1) contains significance levels fordifferences between the means [medians] between sample and control firms. ***significant at the 0.01level; **significant at the 0.05 level; *significant at the 0.10 level.
Hedge Fund TargetSample
(1)
Control Sample
(2)
Earnings and ProfitabilityEPS -0.109***
[-0.018]**0.007
[0.000]
EBITDA [$ million] -127.073**[-4.971]**
31.498[5.068]
ROA -0.019[-0.001]
-0.028[-0.003]
CFO-to-Assets -0.012[-0.003] -0.025[-0.004]
Operating Margin -0.206***[ 0 067]***
-0.073[ 0 010]
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Ability to Pay Off Debt and Interest
Total Debt-to-EBITDA 2.318**
[1.216]***
-4.481[-0.135]
FFO-to-Total Debt 0.065[0.005]
0.058[0.002]
Z-Score -1.622***[-0.016]***
0.847[0.029]
Other
Total Assets -104.157***[-63.381]***
461.186[132.910]
Market-to-Book -0.051[0.000]
-0.106[0.000]
() 0.027**[0.020]**
-0.000[-0.000]
(Unlevered Returns) 0.049**
[0.024]**
-0.002
[-0.001]N 253 253
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Table 5
Regressions of Short- and Long-Run Abnormal Bond Returns
This table reports the results of OLS regressions on the hedge fund target samples abnormal bond returns.The dependent variable in column (1) is the short-run abnormal bond return, and in column (2) is the long-run abnormal bond return. For each variable, the coefficient ( t-statistic) is reported. All data are winsorizedat the 1% and 99% levels. See Appendix for variable definitions. ***significant at the 0.01 level;**significant at the 0.05 level; *significant at the 0.10 level.
Short-Run
Abnormal BondReturns
Long-Run
Abnormal BondReturns
(1) (2)
Intercept0.008(1.04)
0.012(1.14)
Hedge Fund characteristics
Confrontational -0.064***
(-4.59)
-0.039**
(-2.51)Board -0.007
(-1.07)-0.008*(1.70)
Proxy -0.002(-0.44)
0.005(0.32)
M&A -0.062(-0.92)
-0.054(-0.56)
Bond CharacteristicsSubordinated Debt -0.013
(-1.46)-0.010(-0.34)
* **
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Table 6
Short and Long-Run Expropriation of Wealth from Bondholder to Shareholder
This table reports the results of OLS regressions on the hedge fund target samples short- and long-runexcess bond returns. For each variable, the coefficient (t-statistic) is reported. All data are winsorized at the1% and 99% levels. See Appendix for variable definitions. ***significant at the 0.01 level; **significantat the 0.05 level; *significant at the 0.10 level.
Short-Run Excess BondReturns
Long-Run Excess BondReturns
(1) (2) (3) (4)
Intercept -0.014***(-4.43)
-0.007(-0.88)
0.193***(49.79)
0.248***(11.09)
Short-Run Abnormal Stock Returns -0.037***(-3.81)
-0.049***(-2.58)
Long-Run Abnormal Stock Returns -0.028***(-4.67)
-0.035***(-5.02)
Hedge Fund Characteristics
Confrontational -0.051**(-2.40)
-0.064***(-3.38)
Board -0.004(-0.81)
-0.034*(-1.68)
Proxy -0.006(-0.94)
0.001(0.84)
M&A -0.090(-1.44)
-0.000(-0.11)
Bond Characteristics
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Z-Score -0.000(-0.70)
-0.000(-0.70)
Ln (Total Assets) 0.017(1.35) 0.003(0.59)
Market-to-Book -0.012(-0.72)
-0.004(-0.96)
() 0.005(1.24)
0.000(0.14)
(Unlevered Returns) -0.000(-0.10)
-0.003(-1.43)
Earnings Announcement -0.001(-2.10)
Year Dummies No Yes No Yes
Adjusted R2 Value 0.035 0.097 0.012 0.086N= 189 189 193 193
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Table 7
Changes in Credit Ratings
This table stratifies the sample by directional changes in credit ratings within one year of the initial 13Dfiling. Panel A contains the changes in credit rating. Panel B shows the short- and long-run abnormal bondreturns in the period by the subsequent credit rating change. For each variable in Panel B, the mean[median] is reported. See Appendix for variable definitions. All data are winsorized at the 1% and 99%levels. ***significant at the 0.01 level; **significant at the 0.05 level; *significant at the 0.10 level.
Panel A: Changes in Credit Rating within One Year of Initial 13D Filing
Direction of Change Hedge Fund Target Sample
Number (Percentage)
Control Sample
Number (Percentage)
Downgrade 74 (29.3%) 34 (13.4%)
Upgrade 13 (5.1%) 59 (23.3%)
No Change 41 (16.2%) 89 (35.2%)
Stop Rating 125 (49.4%) 71 (28.1%)Total 253 (100%) 253 (100%)
2 Statistic forAssociation betweenRatings
76.80***
Panel B: Abnormal Bond Returns by Subsequent Change in Credit Rating
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51
Figure 1
Raw Bond Returns Surrounding the Initial Schedule 13D Filing by year
-8
-7
-6
-5
-4
-3
-2
-1
0
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
Short-Term Bond Returns
Long-Term Bond Returns
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52
Figure 2
Raw Bond Returns Surrounding the Initial Schedule 13D Filing by Rating
-8
-7
-6
-5
-4
-3
-2
-1
0
A A-
BBB
+BB
B
BBB
-BB
+BB
BB-
B+ B B
-
CCC+
CCC
CCC-
Short-Term Bond Returns
Long-Term Bond Returns
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